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UID:pretalx-sips2025-budapest-BECA9J@pretalx.com
DTSTART;TZID=CET:20250625T102200
DTEND;TZID=CET:20250625T103000
DESCRIPTION:Researchers’ degrees of freedom in data analysis presents sig
 nificant challenges in social sciences\, where different analytical decisi
 ons can lead to varying conclusions. In this work\, we propose a framework
  of an exploratory multiverse simulation to empirically compare various de
 cision pathways to identify how arbitrary analytical decisions affect the 
 conclusions of a study. The framework is demonstrated on the Congruency Se
 quence Effect (CSE)\, a well-studied phenomenon in cognitive control resea
 rch. We reviewed existing literature to identify common non-theory-specifi
 c analytical decisions\, such as outlier exclusion criteria and hypothesis
  testing methods and incorporated these into our simulation framework. Usi
 ng a large number of simulated datasets\, we compared the True Positive Ra
 tes (TPR) and False Positive Rates (FPR)\, and observed effect sizes acros
 s different decision pathways. We recommend this framework as a tool to qu
 antify the impact of different analytical decisions on study conclusions i
 n notable well-studied effects.
DTSTAMP:20260514T165058Z
LOCATION:Underground\, p10
SUMMARY:LT4: An exploratory multiverse simulation framework to assess the i
 mpact of arbitrary analitical decisions - Miklos Bognar
URL:https://pretalx.com/sips2025-budapest/talk/BECA9J/
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